With the rapid growth of multimedia service, quality assessment for visual communication system has becomes more important and has attracted research and industrial attention. In the two main categories of assessment approaches, the subjective assessment, such as Mean Opinion Score (MOS), is very tedious, expensive and difficult to be conducted automatically. The objective metrics based assessments, on the other hand, are more suitable for automatic quality assessment system. Objective visual quality metrics can be divided into three main categories: full-reference (FR) metrics, reduced-reference (RR) metrics and no-reference (NR) metrics. As these names indicate, these three types of quality assessment metrics can be exploited in the system with full availability, limited availability and no availability of the original visual content.
A lot of FR metrics have been investigated in recent years and recommended by ITU. See ITU-T J.144 “Objective perceptual video quality measurement techniques for digital cable television in the presence of a full reference”, Seies J: Cable Networks and Transmission of Television, Sound Programme and Other Multimedia Signals—Measurement of the Quality of Service, March 2003. Though the results are well correlated with the human visual system, it is not very suitable for in-service automatic quality assessment of most visual transmission systems. In most visual communication applications, such as broadcasting TV and video on demand, the original visual content are not available at the point of evaluation. It could be argued that a set of known visual content could give a quality assessment for the visual transmission system. However, unlike voice, most popular image or video compression techniques such as JPEG and MPEG are variable bit rate compression so that the transmission rate is highly dependent on the characteristics of the visual content. The large variation of characteristics from image to image make it hard to emulate the true content for visual transmission system when a problem is reported. Therefore, assessing a set of known images does not provide a good surrogate for assessing the quality of a variable bit rate visual communication. Furthermore, the visual content characteristics also have an impact on transmission and restoration techniques. Therefore, FR visual quality assessment does not easily support a visual communication system quality assessment.
Without the availability of the reference visual content, NR visual quality assessment could provide an alternative. However, this is a very difficult task and is largely unexplored. Currently, NR model has acceptable performance only when the prior knowledge of the types of image distortion or all the components in the transmission system is available. See, for example, Z. Wang and E. P. Simoncelli, REDUCED-REFERENCE IMAGE QUALITY ASSESSMENT USING A WAVELET-DOMAIN NATURAL IMAGE STATISTIC MODEL, Human Vision and Electronic Imaging X, Proc. SPIE, vol. 5666, San Jose, Calif., January 2005; H. R. Sheikh, A. C. Bovik, and L. Cormack, BLIND QUALITY ASSESSMENT OF JPEG2000 COMPRESSED IMAGES USING NATURAL SCENE STATISTICS, Proc. IEEE Asilomar Conf on Signals, Systems, and Computers, November 2003, Pacific Grove, Calif.